A social network is a social structure made of individuals or organizations that are tied by one or more specific types of interdependencies. The resulting structures are often very complex. Social network analysis (SNA) views a social network in terms of a graph with vertices and edges. Vertices are the individual actors within the network, which are generally individuals and organizations. Edges are the relationships between the individual actors, such as values, visions, ideas, financial exchange, friends, kinship, dislike, conflict, trade, web links, business relations, disease transmission, airline routes, etc. SNA is regarded as a powerful tool for determining a variety of social properties of the graph.
SNA is especially useful when applied for social networks spread across multiple sources such us countries, social groups, companies, departments, buildings, etc. The more information from the multiple sources for a distributed social network that can be gathered, the better the SNA results. However, the collection of information for a distributed social network might be restricted by privacy requirements, or enforces data governance policies. An example for such requirements is the variety of privacy protection laws, adopted in most countries and in many international organizations worldwide. Furthermore, virtually all large organizations follow strict internal rules for personal data protection regarding customers, partners, employees, etc. In order to analyze and determine the properties of such networks, what is required is privacy-preserving SNA to protect personally identifiable data from the multiple sources.